Sun Rui created SPARK-12922:
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Summary: Implement gapply() on DataFrame in SparkR
Key: SPARK-12922
URL: https://issues.apache.org/jira/browse/SPARK-12922
Project: Spark
Issue Type: Sub-task
Components: SparkR
Affects Versions: 1.6.0
Reporter: Sun Rui
gapply() applies an R function on groups grouped by one or more columns of a
DataFrame, and returns a DataFrame. It is like GroupedDataSet.flatMapGroups()
in the Dataset API.
Two API styles are supported:
1.
{code}
gd <- groupBy(df, col1, ...)
gapply(gd, function(grouping_key, group) {}, schema)
{code}
2.
{code}
gapply(df, grouping_columns, function(grouping_key, group) {}, schema)
{code}
R function input: grouping keys value
a local data.frame of this grouped data
R function output: local data.frame
Schema specifies the Row format of the output of the R function. It must match
the R function's output.
Note that map-side combination (partial aggregation) is not supported, user
could do map-side combination via dapply().
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